SAR Image Compression Using HVS Model

Author

Aili, Wang ; Ye, Zhang ; Yanfeng, Gu

Author_Institution

Dept. of Electron. & Commun. Eng., Harbin Inst. of Technol.

fYear

2006

fDate

16-19 Oct. 2006

Firstpage

1

Lastpage

4

Abstract

Generally synthetic aperture radar (SAR) image compression methods based on wavelet transform remove statistic redundancy of image data and neglect visual redundancy. In view of this problem, a new image compression method based on human visual system (HVS) is proposed in this paper. First SAR image is decomposed by wavelet transform, then wavelet coefficients in different subbands are weighted by the peak of contrast sensitivity function (CSF) curve in wavelet domain, at last set partitioning in hierarchical trees (SPIHT) algorithm is used to code the weighted wavelet coefficients to form embedded bit stream. Compression results show that comparing with conventional SPIHT algorithm, the method proposed in this paper gets better subject visual quality at the same compression ratio with almost equivalent objective evaluation results

Keywords

data compression; image coding; radar imaging; synthetic aperture radar; trees (mathematics); wavelet transforms; CSF; HVS model; SAR image compression; SPIHT algorithm; contrast sensitivity function; human visual system; set partitioning-in-hierarchical trees; synthetic aperture radar; wavelet transform; Humans; Image coding; Partitioning algorithms; Statistics; Streaming media; Synthetic aperture radar; Visual system; Wavelet coefficients; Wavelet domain; Wavelet transforms; SAR image compression; contrast sensitivity function(CSF); human visual system(HVS); set partitioning in hierarchical trees(SPIHT) algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 2006. CIE '06. International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7803-9582-4

Electronic_ISBN

0-7803-9583-2

Type

conf

DOI

10.1109/ICR.2006.343264

Filename

4148370